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Record W3083097298 · doi:10.1158/1538-7445.am2020-5156

Abstract 5156: Targeting N-myristoylation in B-cell lymphomas as a therapeutic strategy

2020· article· en· W3083097298 on OpenAlexaff
Erwan Beauchamp, Megan C. Yap, Maneka A. Perinpanayagam, Jay M. Gamma, Krista M. Vincent, Raymond Lai, Weifeng Dong, Manikandan Lakshmanan, Anandhkumar Raju, Vinay Tergaonkar, Soo‐Yong Tan, Soon Thye Lim, Lynne‐Marie Postovit, Kevin D. Read, David W. Gray, Paul G. Wyatt, John R. Mackey, Luc G. Berthiaume

Bibliographic record

VenueCancer Research · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMyristoylationCancer researchCell growthSignal transductionMAPK/ERK pathwayCell cultureMCL1B cellBiologyLymphomabreakpoint cluster regionApoptosisIbrutinibCellCHOPViability assayKinaseCell biologyReceptorImmunologyLeukemiaPhosphorylationChronic lymphocytic leukemiaDownregulation and upregulationBiochemistryAntibody

Abstract

fetched live from OpenAlex

Abstract Myristoylation is the N-terminal modification of proteins with the fatty acid myristate. This process is mediated by two ubiquitously expressed N-myristoyltransferases, NMT1 and NMT2, and is critical for membrane targeting and cell signaling. Because NMT expression is increased in some cancers, we used three robotic screens to evaluate the potential of the potent pan-NMT inhibitor PCLX-001 on 300 cancer cell lines spanning the spectrum of human cancers. We discovered a marked increase in the sensitivity of hematological cancer cell lines, including B-cell lymphomas, to myristoylation inhibition. PCLX-001 consistently reduced both lymphoma cell proliferation and viability at concentrations lower than those needed to inhibit the growth of or to kill benign immortalized B cells. In lymphoma cell lines, PCLX-001 treatment inhibited early B-cell receptor (BCR) signaling events by disrupting membrane targeting of several myristoylated Src family kinases and promoted their ubiquitin-mediated degradation. Unexpectedly, PCLX-001 also promoted the degradation of non-myristoylated transcriptional activators P-ERK, c-Myc, NFκB and CREB downstream in the BCR signaling cascade, leading to loss of survival signals and apoptosis. Furthermore, compared to clinically approved drugs dasatinib and ibrutinib, PCLX-001 was more potent in vitro at inhibiting B-cell signaling, had a wider breadth of efficacy, and had greater selectivity thus sparing normal B cells. PCLX-001 treatment reduced tumor size in a time and concentration dependent manner in three B-cell lymphoma xenograft models and resulted in complete disease regression in two of these models, including an R-CHOP refractory lymphoma patient-derived xenograft. To investigate the potential mechanisms responsible for the sensitivity of hematological cancers to PCLX-001, we examined the NMT expression levels in cancer cells using publically available databases. Contrary to the reported NMT overexpression in some cancers, we found that hematological cancer cell lines and tumors both display significant reduction in NMT2 expression. The decreased NMT2 expression is significantly correlated with lower EC50 and poorer patient prognosis. Using the CRISPR-based genetic alteration Cancer Dependency Map, we discovered that cancer cells are highly dependent on functional NMT1, and that NMT1 dependency increases with low NMT2 expression. PCLX-001 treatment may mimic the effect of genetic alteration of NMT1 in hematological cancer cells low in NMT2 by pharmacologically inhibiting the remaining NMT1 in these cells. This results in an effect reminiscent of synthetic lethality since the vast majority of normal cells express both NMTs and PCLX-001 selectively kills NMT2-deficient cancer cells while sparing normal cells. Our findings support the ongoing development and eventual clinical trials of PCLX-001 as a therapy for hematological cancers. Citation Format: Erwan Beauchamp, Megan C. Yap, Maneka A. Perinpanayagam, Jay M. Gamma, Krista M. Vincent, Raymond Lai, Wei-Feng Dong, Manikandan Lakshmanan, Anandhkumar Raju, Vinay Tergaonkar, Soo Yong Tan, Soon Thye Lim, Lynne Postovit, Kevin D. Read, David W. Gray, Paul G. Wyatt, John R. Mackey, Luc G. Berthiaume. Targeting N-myristoylation in B-cell lymphomas as a therapeutic strategy [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5156.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.083
GPT teacher head0.373
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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